1. Field of the Invention
The present invention relates to creating databases where data mining for medical applications, can be performed.
2. Description of the Related Art
Current practices in medical applications are deficient in creating databases which can effectively be used by stakeholders in the healthcare industry.
While healthcare reform remains an important and timely topic for political and economic debate, all parties agree that balancing supply and demand within the delivery of healthcare services is critical to long term success. Unfortunately, the majority of healthcare consumers and service providers have very little understanding as to how physician reimbursements are calculated and modified, as medical practice trends and supporting technologies rapidly evolve.
Thus, while Pay for Performance (P4P) and Evidence-Based Medicine (EBM), which include data standardization and accessibility, and financial incentives tied to quality improvement, are standard, one could argue that the current reimbursement does not go far enough, and that a number of deficiencies exist related to transparency, accountability, accessibility, and quality. Accordingly, as the tenets of EBM and P4P become engrained within healthcare delivery, it is essential to modify the existing reimbursement model to reflect these principles. The opportunity to accomplish this goal is advanced through the continued evolution of information systems technologies and data mining. Thus, incorporating objective and standardized data into a transparent and accessible database, which can be used to enhance performance, education, and informed decision making, is needed.
In another problem associated with current practices, with the above stated continuing efforts to reduce medical reimbursements, many radiology service providers have reacted by increasing productivity, in order to maintain revenue. This continuing push to increase speed carries the risk of diminished quality, in the form of diagnostic accuracy. Thus, synergistically improving both productivity and quality, through the combined analysis of examination complexity, interpretation accuracy, and interpretation times, specific to each individual radiologist, is needed.
Finally, in another problem associated with current practices, EBM calls for the creation of “best practice” guidelines, leading to improved clinical outcomes, but one of the primary factors limiting EBM in radiology is the relative paucity of standardized databases. The creation of standardized medical imaging databases would offer the potential to enhance radiologist workflow and diagnostic accuracy through objective data-driven analytics; which can be categorized in accordance with specific variables relating to the individual exam, patient, provider, and technology being utilized.
Thus, the use of data mining in medical applications to solve all three issues, would greatly benefit diagnostic accuracy, workflow, and accountability.